

import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		lowercase			:				List[str]   =     None


lowercase			:				Optional[Any]   =     logging.get_logger(__name__)


lowercase			:				str   =     {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase			:				Tuple   =     {
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

lowercase			:				Dict   =     {
    "facebook/mbart-large-en-ro": 10_24,
    "facebook/mbart-large-cc25": 10_24,
}

# fmt: off
lowercase			:				str   =     ["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN"]







class 					__lowercase  (						_SCREAMING_SNAKE_CASE				):





							"""simple docstring"""

							UpperCAmelCase_						:		Tuple								=	VOCAB_FILES_NAMES
							UpperCAmelCase_						:		Dict								=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCAmelCase_						:		int								=	PRETRAINED_VOCAB_FILES_MAP
							UpperCAmelCase_						:		str								=	['''input_ids''', '''attention_mask''']
							UpperCAmelCase_						:		List[Any]								=	MBartTokenizer

							UpperCAmelCase_						:		List[int]								=	[]
							UpperCAmelCase_						:		List[int]								=	[]




							def __init__(					self    ,						__UpperCAmelCase=None    ,						__UpperCAmelCase=None    ,						__UpperCAmelCase="<s>"    ,						__UpperCAmelCase="</s>"    ,						__UpperCAmelCase="</s>"    ,						__UpperCAmelCase="<s>"    ,						__UpperCAmelCase="<unk>"    ,						__UpperCAmelCase="<pad>"    ,						__UpperCAmelCase="<mask>"    ,						__UpperCAmelCase=None    ,						__UpperCAmelCase=None    ,						__UpperCAmelCase=None    ,						**__UpperCAmelCase    ,						)		->       Optional[Any]:
														# Mask token behave like a normal word, i.e. include the space before it
														A      :					List[str]      		=					AddedToken(__UpperCAmelCase    ,						lstrip=__UpperCAmelCase    ,						rstrip=__UpperCAmelCase						) if isinstance(__UpperCAmelCase    ,						__UpperCAmelCase						) else mask_token

														super().__init__(
														    vocab_file=__UpperCAmelCase    ,						tokenizer_file=__UpperCAmelCase    ,						bos_token=__UpperCAmelCase    ,						eos_token=__UpperCAmelCase    ,						sep_token=__UpperCAmelCase    ,						cls_token=__UpperCAmelCase    ,						unk_token=__UpperCAmelCase    ,						pad_token=__UpperCAmelCase    ,						mask_token=__UpperCAmelCase    ,						src_lang=__UpperCAmelCase    ,						tgt_lang=__UpperCAmelCase    ,						additional_special_tokens=__UpperCAmelCase    ,						**__UpperCAmelCase    ,						)

														A      :					Union[str, Any]      		=					vocab_file
														A      :					Optional[int]      		=					False if not self.vocab_file else True

														A      :					str      		=					FAIRSEQ_LANGUAGE_CODES.copy()

														if additional_special_tokens is not None:
																					# Only add those special tokens if they are not already there.
																					_additional_special_tokens.extend(
																					    [t for t in additional_special_tokens if t not in _additional_special_tokens]						)

														self.add_special_tokens({'''additional_special_tokens''': _additional_special_tokens}						)
														A      :					Tuple      		=					{
														    lang_code: self.convert_tokens_to_ids(__UpperCAmelCase						) for lang_code in FAIRSEQ_LANGUAGE_CODES
														}

														A      :					Union[str, Any]      		=					src_lang if src_lang is not None else '''en_XX'''
														A      :					Optional[Any]      		=					self.convert_tokens_to_ids(self._src_lang						)
														A      :					Tuple      		=					tgt_lang
														self.set_src_lang_special_tokens(self._src_lang						)




							@property
							def       snake_case			(					self						)		->       str:
														return self._src_lang




							@src_lang.setter
							def       snake_case			(					self    ,						__UpperCAmelCase						)		->       None:
														A      :					List[Any]      		=					new_src_lang
														self.set_src_lang_special_tokens(self._src_lang						)




							def       snake_case			(					self    ,						__UpperCAmelCase    ,						__UpperCAmelCase = None						)		->       List[int]:
														if token_ids_a is None:
																					return self.prefix_tokens + token_ids_a + self.suffix_tokens
														# We don't expect to process pairs, but leave the pair logic for API consistency
														return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




							def       snake_case			(					self    ,						__UpperCAmelCase    ,						__UpperCAmelCase = None						)		->       List[int]:
														A      :					Dict      		=					[self.sep_token_id]
														A      :					str      		=					[self.cls_token_id]

														if token_ids_a is None:
																					return len(cls + token_ids_a + sep						) * [0]
														return len(cls + token_ids_a + sep + sep + token_ids_a + sep						) * [0]




							def       snake_case			(					self    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						**__UpperCAmelCase						)		->       Optional[int]:
														if src_lang is None or tgt_lang is None:
																					raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''						)
														A      :					Tuple      		=					src_lang
														A      :					Tuple      		=					self(__UpperCAmelCase    ,						add_special_tokens=__UpperCAmelCase    ,						return_tensors=__UpperCAmelCase    ,						**__UpperCAmelCase						)
														A      :					List[str]      		=					self.convert_tokens_to_ids(__UpperCAmelCase						)
														A      :					str      		=					tgt_lang_id
														return inputs




							def       snake_case			(					self    ,						__UpperCAmelCase    ,						__UpperCAmelCase = "en_XX"    ,						__UpperCAmelCase = None    ,						__UpperCAmelCase = "ro_RO"    ,						**__UpperCAmelCase    ,						)		->       BatchEncoding:
														A      :					Optional[int]      		=					src_lang
														A      :					List[str]      		=					tgt_lang
														return super().prepare_seqaseq_batch(__UpperCAmelCase    ,						__UpperCAmelCase    ,						**__UpperCAmelCase						)




							def       snake_case			(					self						)		->       List[str]:
														return self.set_src_lang_special_tokens(self.src_lang						)




							def       snake_case			(					self						)		->       Union[str, Any]:
														return self.set_tgt_lang_special_tokens(self.tgt_lang						)




							def       snake_case			(					self    ,						__UpperCAmelCase						)		->       None:
														A      :					int      		=					self.convert_tokens_to_ids(__UpperCAmelCase						)
														A      :					Any      		=					[]
														A      :					Union[str, Any]      		=					[self.eos_token_id, self.cur_lang_code]

														A      :					List[str]      		=					self.convert_ids_to_tokens(self.prefix_tokens						)
														A      :					Optional[int]      		=					self.convert_ids_to_tokens(self.suffix_tokens						)

														A      :					Any      		=					processors.TemplateProcessing(
														    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str    ,						pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str    ,						special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str    ,						self.prefix_tokens + self.suffix_tokens						)						)    ,						)




							def       snake_case			(					self    ,						__UpperCAmelCase						)		->       None:
														A      :					Any      		=					self.convert_tokens_to_ids(__UpperCAmelCase						)
														A      :					List[Any]      		=					[]
														A      :					Tuple      		=					[self.eos_token_id, self.cur_lang_code]

														A      :					Dict      		=					self.convert_ids_to_tokens(self.prefix_tokens						)
														A      :					Optional[Any]      		=					self.convert_ids_to_tokens(self.suffix_tokens						)

														A      :					Dict      		=					processors.TemplateProcessing(
														    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str    ,						pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str    ,						special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str    ,						self.prefix_tokens + self.suffix_tokens						)						)    ,						)






							def       snake_case			(					self    ,						__UpperCAmelCase    ,						__UpperCAmelCase = None						)		->       Tuple[str]:
														if not self.can_save_slow_tokenizer:
																					raise ValueError(
																					    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
																					    '''tokenizer.'''						)

														if not os.path.isdir(__UpperCAmelCase						):
																					logger.error(f'Vocabulary path ({save_directory}) should be a directory.'						)
																					return
														A      :					Union[str, Any]      		=					os.path.join(
														    __UpperCAmelCase    ,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

														if os.path.abspath(self.vocab_file						) != os.path.abspath(__UpperCAmelCase						):
																					copyfile(self.vocab_file    ,						__UpperCAmelCase						)

														return (out_vocab_file,)









from ..utils import DummyObject, requires_backends







class 					__lowercase  (						metaclass=_SCREAMING_SNAKE_CASE				):





							"""simple docstring"""

							UpperCAmelCase_						:		Optional[Any]								=	['''speech''']




							def __init__(					self    ,						*__UpperCAmelCase    ,						**__UpperCAmelCase						)		->       Dict:
														requires_backends(self    ,						['''speech''']						)







class 					__lowercase  (						metaclass=_SCREAMING_SNAKE_CASE				):





							"""simple docstring"""

							UpperCAmelCase_						:		int								=	['''speech''']




							def __init__(					self    ,						*__UpperCAmelCase    ,						**__UpperCAmelCase						)		->       Tuple:
														requires_backends(self    ,						['''speech''']						)






